The red palm weevil (RPW), Rhynchophorus ferrugineus (Olivier), also known as the Asian palm weevil, is an invasive pest that causes widespread damage to palm trees around the globe. As pheromone communication is crucial for their mass attack and survival on palm trees, the olfactory concept of pest control strategies has been widely explored recently. We aim to understand the molecular basis of olfaction in RPW by studying one of the key olfactory proteins in insect pheromone communication, sensory neuron membrane proteins (SNMPs). SNMPs belong to the CD36 (cluster of differentiation 36) family that perform two distinct olfactory roles in insects, either in pheromone (odorant) transfer to the odorant receptors (SNMP1) or in the pheromone clearing process (SNMP2). In this study, we performed antennal transcriptomic screening and identified six SNMPs, mapping them on the R. ferrugineus genome, and confirmed four distinct SNMPs. Both SNMP1 proteins in RPW, viz., RferSNMPu1 and RferSNMPu2, were mapped onto the same scaffold in different loci in the RPW genome. To further understand the function of these proteins, we first classified them using phylogenetic analysis and checked their tissue-specific expression patterns. Further, we measured the relative transcript abundance of SNMPs in laboratory-reared, field-collected adults and pheromone-exposure experiments, ultimately identifying RferSNMPu1 as a potential candidate for functional analysis. We mapped RferSNMPu1 expression in the antennae and found that expression patterns were similar in both sexes. We used RNAi-based gene silencing to knockdown RferSNMPu1 and tested the changes in the RPW responses to aggregation pheromone compounds, 4-methyl-5-nonanol (ferrugineol) and 4-methyl-5-nonanone (ferrugineone), and a kairomone, ethyl acetate using electroantennogram (EAG) recordings. We found a significant reduction in the EAG recordings in the RferSNMPu1 knockdown strain of adult RPWs, confirming its potential role in pheromone detection. The structural modelling revealed the key domains in the RferSNMPu1 structure, which could likely be involved in pheromone detection based on the identified ectodomain tunnels. Our studies on RferSNMPu1 with a putative role in pheromone detection provide valuable insight into understanding the olfaction in R. ferrugineus as well as in other Curculionids, as SNMPs are under-explored in terms of its functional role in insect olfaction. Most importantly, RferSNMPu1 can be used as a potential target for the olfactory communication disruption in the R. ferrugineus control strategies.

• Keywords
• Electrophysiology, Olfaction, Palm weevil, Pest control, RNAi, Sensory neuron membrane protein,
• MeSH
• Pheromones * metabolism   MeSH
• Phylogeny MeSH
• Insect Proteins * genetics   metabolism   MeSH
• Membrane Proteins metabolism   genetics   MeSH
• Sensory Receptor Cells metabolism   MeSH
• Weevils * metabolism   genetics   MeSH
• Receptors, Odorant genetics   metabolism   MeSH
• Arthropod Antennae metabolism   MeSH
• Gene Silencing MeSH
• Animals MeSH
• Check Tag
• Male MeSH
• Female MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Pheromones * MeSH
• Insect Proteins * MeSH
• Membrane Proteins MeSH
• Receptors, Odorant MeSH

HaloTag labeling technology has introduced unrivaled potential in protein chemistry and molecular and cellular biology. A wide variety of ligands have been developed to meet the specific needs of diverse applications, but only a single protein tag, DhaAHT, is routinely used for their incorporation. Following a systematic kinetic and computational analysis of different reporters, a tetramethylrhodamine- and three 4-stilbazolium-based fluorescent ligands, we showed that the mechanism of incorporating different ligands depends both on the binding step and the efficiency of the chemical reaction. By studying the different haloalkane dehalogenases DhaA, LinB, and DmmA, we found that the architecture of the access tunnels is critical for the kinetics of both steps and the ligand specificity. We showed that highly efficient labeling with specific ligands is achievable with natural dehalogenases. We propose a simple protocol for selecting the optimal protein tag for a specific ligand from the wide pool of available enzymes with diverse access tunnel architectures. The application of this protocol eliminates the need for expensive and laborious protein engineering.

• Publication type
• Journal Article MeSH

Protein dynamics are often invoked in explanations of enzyme catalysis, but their design has proven elusive. Here we track the role of dynamics in evolution, starting from the evolvable and thermostable ancestral protein AncHLD-RLuc which catalyses both dehalogenase and luciferase reactions. Insertion-deletion (InDel) backbone mutagenesis of AncHLD-RLuc challenged the scaffold dynamics. Screening for both activities reveals InDel mutations localized in three distinct regions that lead to altered protein dynamics (based on crystallographic B-factors, hydrogen exchange, and molecular dynamics simulations). An anisotropic network model highlights the importance of the conformational flexibility of a loop-helix fragment of Renilla luciferases for ligand binding. Transplantation of this dynamic fragment leads to lower product inhibition and highly stable glow-type bioluminescence. The success of our approach suggests that a strategy comprising (i) constructing a stable and evolvable template, (ii) mapping functional regions by backbone mutagenesis, and (iii) transplantation of dynamic features, can lead to functionally innovative proteins.

• MeSH
• NIH 3T3 Cells MeSH
• Catalysis MeSH
• Kinetics MeSH
• Protein Conformation MeSH
• Luciferases, Renilla chemistry   genetics   metabolism   MeSH
• Luciferases chemistry   genetics   metabolism   MeSH
• Mutation MeSH
• Mutagenesis MeSH
• Mice MeSH
• Protein Engineering * MeSH
• Mammals MeSH
• Molecular Dynamics Simulation * MeSH
• Enzyme Stability MeSH
• Temperature MeSH
• Binding Sites MeSH
• Animals MeSH
• Check Tag
• Mice MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Luciferases, Renilla MeSH
• Luciferases MeSH

Interactions between enzymes and small molecules lie in the center of many fundamental biochemical processes. Their analysis using molecular dynamics simulations have high computational demands, geometric approaches fail to consider chemical forces, and molecular docking offers only static information. Recently, we proposed to combine molecular docking and geometric approaches in an application called CaverDock. CaverDock is discretizing enzyme tunnel into discs, iteratively docking with restraints into one disc after another and searching for a trajectory of the ligand passing through the tunnel. Here, we focus on the practical side of its usage describing the whole method: from getting the application, and processing the data through a workflow, to interpreting the results. Moreover, we shared the best practices, recommended how to solve the most common issues, and demonstrated its application on three use cases.

• Keywords
• Drug design, Enzyme engineering, Ligand screening, Ligand transport, Molecular docking, Tunnel analysis,
• MeSH
• Chlorohydrins chemistry   MeSH
• Ethanol analogs & derivatives   chemistry   MeSH
• Ethylene Dibromide chemistry   MeSH
• Hydrolases chemistry   MeSH
• Arachidonic Acid chemistry   MeSH
• Ligands MeSH
• Drug Discovery methods   MeSH
• Proteins chemistry   MeSH
• Drug Design MeSH
• Molecular Dynamics Simulation MeSH
• Molecular Docking Simulation methods   MeSH
• Software MeSH
• Cytochrome P-450 Enzyme System chemistry   MeSH
• Thermodynamics MeSH
• Protein Binding MeSH
• Binding Sites MeSH
• Structure-Activity Relationship MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• 2,3-dichloro-1-propanol MeSH Browser
• Chlorohydrins MeSH
• Ethanol MeSH
• Ethylene Dibromide MeSH
• ethylene bromohydrin MeSH Browser
• haloalkane dehalogenase MeSH Browser
• Hydrolases MeSH
• Arachidonic Acid MeSH
• Ligands MeSH
• Proteins MeSH
• Cytochrome P-450 Enzyme System MeSH

N-terminal acetyltransferases (NATs) belong to the superfamily of acetyltransferases. They are enzymes catalysing the transfer of an acetyl group from acetyl coenzyme A to the N-terminus of polypeptide chains. N-terminal acetylation is one of the most common protein modifications. To date, not much is known on the molecular basis for the exclusive substrate specificity of NATs. All NATs share a common fold called GNAT. A characteristic of NATs is the β6β7 hairpin loop covering the active site and forming with the α1α2 loop a narrow tunnel surrounding the catalytic site in which cofactor and polypeptide meet and exchange an acetyl group. We investigated the dynamics-function relationships of all available structures of NATs covering the three domains of Life. Using an elastic network model and normal mode analysis, we found a common dynamics pattern conserved through the GNAT fold; a rigid V-shaped groove formed by the β4 and β5 strands and splitting the fold in two dynamical subdomains. Loops α1α2, β3β4 and β6β7 all show clear displacements in the low frequency normal modes. We characterized the mobility of the loops and show that even limited conformational changes of the loops along the low-frequency modes are able to significantly change the size and shape of the ligand binding sites. Based on the fact that these movements are present in most low-frequency modes, and common to all NATs, we suggest that the α1α2 and β6β7 loops may regulate ligand uptake and the release of the acetylated polypeptide.

• Keywords
• Acetylation, Ligand specificity, N-terminal acetyltransferases, Normal modes analysis, Protein dynamics,
• Publication type
• Journal Article MeSH

Caver Web 1.0 is a web server for comprehensive analysis of protein tunnels and channels, and study of the ligands' transport through these transport pathways. Caver Web is the first interactive tool allowing both the analyses within a single graphical user interface. The server is built on top of the abundantly used tunnel detection tool Caver 3.02 and CaverDock 1.0 enabling the study of the ligand transport. The program is easy-to-use as the only required inputs are a protein structure for a tunnel identification and a list of ligands for the transport analysis. The automated guidance procedures assist the users to set up the calculation in a way to obtain biologically relevant results. The identified tunnels, their properties, energy profiles and trajectories for ligands' passages can be calculated and visualized. The tool is very fast (2-20 min per job) and is applicable even for virtual screening purposes. Its simple setup and comprehensive graphical user interface make the tool accessible for a broad scientific community. The server is freely available at https://loschmidt.chemi.muni.cz/caverweb.

• MeSH
• Algorithms * MeSH
• Benchmarking MeSH
• Protein Interaction Domains and Motifs MeSH
• Internet MeSH
• Protein Structure, Quaternary MeSH
• Humans MeSH
• Ligands MeSH
• Amino Acid Sequence MeSH
• Molecular Docking Simulation MeSH
• Protein Structure, Tertiary MeSH
• Carrier Proteins chemistry   metabolism   MeSH
• User-Computer Interface * MeSH
• Protein Binding MeSH
• Binding Sites MeSH
• Computational Biology methods   MeSH
• Animals MeSH
• Check Tag
• Humans MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Ligands MeSH
• Carrier Proteins MeSH